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Introduction

This is just another wrapper for highcharts javascript library for R. The mainly motivation to this packages is get a the all the power from HCs API with no restrictions and write the plots using the pipe operator just like metricsgraphics and dygraphs.

Highcharts is very mature javascript charting library and it has a great and powerful API to get a very style of charts and highly customized (see http://www.highcharts.com/demo).

In the package there’s some partial implementation of the HC API in R like hc_title, hc_add_series, hc_xAxis, and some shorcuts to made simples chart in R like hc_add_series_scatter, hc_add_series_scatter by if you want you can create your chart manually with all the requiriments what you need. That’s the package offer.

Why another?

The main reasons is have a wrapper to chart data using piping style.
Include other HC funcionalities like themes and options.
Generate shortcuts to plots some R objects like time series or treemaps.

Installation

You can install the package with the usual install.packages("highcharter") or if you want to try new features before the updates: via devtools devtools::install_github("jbkunst/highcharter").

4 Key parts of the package

I think there are 4 key parts to work with this package:

The implementation of Highcharts API. You can chart almost every type using the api. You need to translate the R objects to (json|list)-like paramter. So it is a must know how highcharts works to take advantage of this package.
The shortcuts functions: Functions to add in a simple way some R objects like xts, ohlc, heatmaps (and more comming soon).
The hchart() function. This function can chart various R objects on the fly with one line of code. The resulting chart is a highchart object so you can keep modifying with the API.
Themes. Highcharts is super really flexible to add and create theme. So why dont implement?

Demo

Highcharts

Let’s start doing a simple column chart:

library("highcharter")

hc <- highchart() %>% 
  hc_title(text = "A nice chart") %>% 
  hc_add_series(data = c(7.0, 6.9, 9.5, 14.5, 18.2, 21.5, 25.2,
                        26.5, 23.3, 18.3, 13.9, 9.6))

hc

If you are not familiar with the magrittr pipe operator (%>%), here is the equivalent without using pipes:

hc <- highchart()
hc <- hc_title(hc, text = "A nice chart")
hc <- hc_add_series(hc, data = c(7.0, 6.9, 9.5, 14.5, 18.2, 21.5, 25.2, 
                                26.5, 23.3, 18.3, 13.9, 9.6))

hc

With the implemented API you can modify the previous chart in a easy way. Let’s do some changes:

Edit style the title.
Add a subtitle with some style.
Add xAxis categories
Add another data (in HC this is call a serie) with some customizations.
Put a shared tooltip.
Put some bands inspired in http://www.highcharts.com/demo/spline-plot-bands.

hc <- hc %>% 
  hc_title(style = list(color = "red")) %>% 
  hc_subtitle(text = "I want to add a subtitle too with style",
              style = list(color = "#B71C1C", fontWeight = "bold")) %>% 
  hc_xAxis(categories = c("Jan", "Feb", "Mar", "Apr", "May", "Jun",
                          "Jul", "Aug", "Sep", "Oct", "Nov", "Dec")) %>% 
  hc_add_series(name = "A another data", type = "column", color = "#1FA67A",
               dataLabels = list(align = "center", enabled = TRUE),
               data = c(3.9, 4.2, 5.7, 8.5, 11.9, 15.2,
                        17.0, 16.6, 14.2, 10.3, 6.6, 4.8)) %>% 
  hc_tooltip(crosshairs = TRUE, shared = TRUE) %>% 
  hc_yAxis(minorGridLineWidth = 0, gridLineWidth = 0,
           plotBands = list(
             list(from = 20, to = 30, color = "rgba(68, 170, 213, 0.1)",
                  label = list(text = "A band from 20 to 30")),
             list(from = 10, to = 20, color = "rgba(0, 0, 0, 0.1)",
                  label = list(text = "Another band"))
             ))

hc

Easy right? Well, it’s just the Highcharts API. Thanks to the http://www.highcharts.com/ team.

Highstocks

library("quantmod")

x <- getSymbols("AAPL", auto.assign = FALSE)
y <- getSymbols("AMZN", auto.assign = FALSE)
z <- getSymbols("YHOO", auto.assign = FALSE)

highchart() %>% 
  hc_add_series_ohlc(x) %>% 
  hc_add_series_ohlc(y, type = "ohlc") %>% 
  hc_add_series_ohlc(z, type = "line")

Highmaps

library("viridisLite")
library("dplyr")
data(unemployment)
data(uscountygeojson)

dclass <- data_frame(from = seq(0, 10, by = 2),
                     to = c(seq(2, 10, by = 2), 50),
                     color = substring(viridis(length(from), option = "C"), 0, 7))
dclass <- list.parse3(dclass)

highchart() %>% 
  hc_title(text = "US Counties unemployment rates, April 2015") %>% 
  hc_add_series_map(uscountygeojson, unemployment,
                    value = "value", joinBy = "code") %>% 
  hc_colorAxis(dataClasses = dclass) %>% 
  hc_legend(layout = "vertical", align = "right",
             floating = TRUE, valueDecimals = 0,
             valueSuffix = "%") %>% 
  hc_mapNavigation(enabled = TRUE)

The higcharts API (and this wrapper)

Premise: There’s not default arguments. All arguments need to be named.

Let’s use a simple plot to show how do with the differentes funcions from the package.

data(citytemp)

citytemp

month	tokyo	new_york	berlin	london
Jan	7.0	-0.2	-0.9	3.9
Feb	6.9	0.8	0.6	4.2
Mar	9.5	5.7	3.5	5.7
Apr	14.5	11.3	8.4	8.5
May	18.2	17.0	13.5	11.9
Jun	21.5	22.0	17.0	15.2
Jul	25.2	24.8	18.6	17.0
Aug	26.5	24.1	17.9	16.6
Sep	23.3	20.1	14.3	14.2
Oct	18.3	14.1	9.0	10.3
Nov	13.9	8.6	3.9	6.6
Dec	9.6	2.5	1.0	4.8


hc <- highchart() %>% 
  hc_xAxis(categories = citytemp$month) %>% 
  hc_add_series(name = "Tokyo", data = citytemp$tokyo) %>% 
  hc_add_series(name = "London", data = citytemp$london) %>% 
  hc_add_series(name = "Other city",
               data = (citytemp$tokyo + citytemp$london)/2)

hc

hc_chart

With hc_chart you can define general chart options.

hc %>% 
  hc_chart(borderColor = '#EBBA95',
           borderRadius = 10,
           borderWidth = 2,
           backgroundColor = list(
             linearGradient = c(0, 0, 500, 500),
             stops = list(
               list(0, 'rgb(255, 255, 255)'),
               list(1, 'rgb(200, 200, 255)')
             )))

Now change type to colum and add 3d effect.

hc <- hc %>% 
  hc_chart(type = "column",
           options3d = list(enabled = TRUE, beta = 15, alpha = 15))

hc

Now remove 3deffect and add the original type to work with the next examples.

hc <- hc_chart(hc, type = "line", options3d = list(enabled = FALSE))

hc_xAxis and hc_yAxis

This functions allow between other things:

Modify the gridlines.
Add plotBands or plotLines to remark some information.
Show in the opposite side the axis.

hc %>% 
  hc_xAxis(title = list(text = "Month in x Axis"),
           opposite = TRUE,
           plotLines = list(
             list(label = list(text = "This is a plotLine"),
                  color = "#FF0000",
                  width = 2,
                  value = 5.5))) %>% 
  hc_yAxis(title = list(text = "Temperature in y Axis"),
           opposite = TRUE,
           minorTickInterval = "auto",
           minorGridLineDashStyle = "LongDashDotDot",
           showFirstLabel = FALSE,
           showLastLabel = FALSE,
           plotBands = list(
             list(from = 25, to = htmlwidgets::JS("Infinity"), color = "rgba(100, 0, 0, 0.1)",
                  label = list(text = "This is a plotBand"))))

hc_add_series and hc_rm_series

hc <- highchart() %>% 
  hc_xAxis(categories = citytemp$month) %>% 
  hc_add_series(name = "Tokyo", data = citytemp$tokyo) %>% 
  hc_add_series(name = "New York", data = citytemp$new_york) 

hc


hc %>% 
  hc_add_series(name = "London", data = citytemp$london, type = "area") %>% 
  hc_rm_series(name = "New York")

hc_title, hc_subtitle, hc_credits and hc_legend, hc_tooltip, hc_exporting

Functions to modify the chart’s main title, subtitle, credits, legend and tooltip.

hc %>% 
  hc_title(text = "This is a title with <i>margin</i> and <b>Strong or bold text</b>",
           margin = 20, align = "left",
           style = list(color = "#90ed7d", useHTML = TRUE)) %>% 
  hc_subtitle(text = "And this is a subtitle with more information",
              align = "left",
              style = list(color = "#2b908f", fontWeight = "bold")) %>% 
  hc_credits(enabled = TRUE, # add credits
             text = "www.lonk.tomy.site",
             href = "http://jkunst.com") %>% 
  hc_legend(align = "left", verticalAlign = "top",
            layout = "vertical", x = 0, y = 100) %>%
  hc_tooltip(crosshairs = TRUE, backgroundColor = "#FCFFC5",
             shared = TRUE, borderWidth = 5) %>% 
  hc_exporting(enabled = TRUE) # enable exporting option

Shorcuts for add Data (data series)

Scatter

highchart() %>% 
  hc_title(text = "Simple scatter chart") %>% 
  hc_add_series_scatter(mtcars$wt, mtcars$mpg)


highchart() %>% 
  hc_title(text = "Scatter chart with color") %>% 
  hc_add_series_scatter(mtcars$wt, mtcars$mpg,
                       color = mtcars$hp)


highchart() %>% 
  hc_title(text = "Scatter chart with size") %>% 
  hc_add_series_scatter(mtcars$wt, mtcars$mpg,
                       mtcars$drat)


highchart() %>% 
  hc_title(text = "Scatter chart with size and color") %>% 
  hc_add_series_scatter(mtcars$wt, mtcars$mpg,
                       mtcars$drat, mtcars$hp)


highchart(height = 500) %>% 
  hc_title(text = "A complete example for Scatter") %>% 
  hc_add_series_scatter(mtcars$wt, mtcars$mpg,
                       mtcars$drat, mtcars$hp,
                       rownames(mtcars),
                       dataLabels = list(
                         enabled = TRUE,
                         format = "{point.label}"
                       )) %>% 
  hc_chart(zoomType = "xy") %>% 
  hc_tooltip(useHTML = TRUE,
             headerFormat = "<table>",
             pointFormat = paste("<tr><th colspan=\"1\"><b>{point.label}</b></th></tr>",
                                 "<tr><th>Weight</th><td>{point.x} lb/1000</td></tr>",
                                 "<tr><th>MPG</th><td>{point.y} mpg</td></tr>",
                                 "<tr><th>Drat</th><td>{point.z} </td></tr>",
                                 "<tr><th>HP</th><td>{point.valuecolor} hp</td></tr>"),
             footerFormat = "</table>")

Or we can add series one by one.

hc <- highchart()
for (cyl in unique(mtcars$cyl)) {
  hc <- hc %>%
    hc_add_series_scatter(mtcars$wt[mtcars$cyl == cyl],
                         mtcars$mpg[mtcars$cyl == cyl],
                         name = sprintf("Cyl %s", cyl),
                         showInLegend = TRUE)
}

hc

Time Series

If you use time series object with Hicharts you can enabled the Highstock which include sophisticated navigation options like a small navigator series, preset date ranges, date picker, scrolling and panning.

From times and values

data(economics, package = "ggplot2")

highchart() %>% 
  hc_add_series_times_values(economics$date, economics$psavert, 
                             name = "Personal Savings Rate")

Same data but using highstock instead of highcharts.

highchart(type = "stock") %>% 
  hc_title(text = "US economic time series") %>% 
  hc_subtitle(text = "This dataset was produced from US economic time series data available") %>% 
  hc_tooltip(valueDecimals = 2) %>% 
  hc_add_series_times_values(economics$date,
                             economics$psavert,
                             name = "Personal savings rate") %>% 
  hc_add_series_times_values(economics$date,
                             economics$uempmed,
                             name = "Median duration of unemployment") %>% 
  hc_add_theme(hc_theme_sandsignika()) # see more about themes below.

From `ts` objects

There’s a hc_add_series_ts which recieve a ts object.

highchart() %>%
  hc_add_series_ts(AirPassengers, color = "#26838E")


highchart(type = "stock") %>% 
  hc_title(text = "Monthly Deaths from Lung Diseases in the UK") %>% 
  hc_subtitle(text = "Deaths from bronchitis, emphysema and asthma") %>% 
  hc_add_series_ts(fdeaths, name = "Female") %>%
  hc_add_series_ts(mdeaths, name = "Male")

From `xts` objects

Support ohlc series from the quantmod package. You can also add markes or flag with hc_add_series_flags:

library("quantmod")

x <- getSymbols("AAPL", auto.assign = FALSE)
y <- getSymbols("SPY", auto.assign = FALSE)

highchart() %>% 
  hc_add_series_ohlc(x) %>% 
  hc_add_series_ohlc(y)



usdjpy <- getSymbols("USD/JPY", src = "oanda", auto.assign = FALSE)
eurkpw <- getSymbols("EUR/KPW", src = "oanda", auto.assign = FALSE)

dates <- as.Date(c("2015-05-08", "2015-09-12"), format = "%Y-%m-%d")

highchart(type = "stock") %>% 
  hc_add_series_xts(usdjpy, id = "usdjpy") %>% 
  hc_add_series_xts(eurkpw, id = "eurkpw") %>% 
  hc_add_series_flags(dates, title = c("E1", "E2"), 
                      text = c("This is event 1",
                               "This is the event 2"),
                      id = "usdjpy") %>% 
  hc_rangeSelector(inputEnabled = FALSE) %>% 
  hc_scrollbar(enabled = FALSE) %>% 
  hc_add_theme(hc_theme_gridlight())

Treemaps

Here we use the treemap package to create a treemap object and then we create the same treemap via highcharts ;).

library("treemap")
library("viridisLite")

data(GNI2010)

tm <- treemap(GNI2010, index = c("continent", "iso3"),
              vSize = "population", vColor = "GNI",
              type = "value", palette = viridis(6))


hc_tm <- highchart(height = 800) %>% 
  hc_add_series_treemap(tm, allowDrillToNode = TRUE,
                       layoutAlgorithm = "squarified",
                       name = "tmdata") %>% 
  hc_title(text = "Gross National Income World Data") %>% 
  hc_tooltip(pointFormat = "<b>{point.name}</b>:<br>
             Pop: {point.value:,.0f}<br>
             GNI: {point.valuecolor:,.0f}")

hc_tm


hc_tm <- hc_rm_series(hc_tm, name = "tmdata")

Change the type parameter.

tm <- treemap(GNI2010, index = c("continent", "iso3"),
              vSize = "population", vColor = "GNI",
              type = "comp", palette = rev(viridis(6)))


hc_tm %>% 
  hc_add_series_treemap(tm, allowDrillToNode = TRUE,
                       layoutAlgorithm = "squarified")

Labels & Values

data("favorite_bars")
data("favorite_pies")

highchart() %>% 
  hc_title(text = "This is a bar graph describing my favorite pies
           including a pie chart describing my favorite bars") %>%
  hc_subtitle(text = "In percentage of tastiness and awesomeness") %>% 
  hc_add_series_labels_values(favorite_pies$pie, favorite_pies$percent, name = "Pie",
                              colorByPoint = TRUE, type = "column") %>% 
  hc_add_series_labels_values(favorite_bars$bar, favorite_bars$percent,
                              colors = substr(terrain.colors(5), 0 , 7), type = "pie",
                              name = "Bar", colorByPoint = TRUE, center = c('35%', '10%'),
                              size = 100, dataLabels = list(enabled = FALSE)) %>% 
  hc_yAxis(title = list(text = "percentage of tastiness"),
           labels = list(format = "{value}%"), max = 100) %>% 
  hc_xAxis(categories = favorite_pies$pie) %>% 
  hc_legend(enabled = FALSE) %>% 
  hc_tooltip(pointFormat = "{point.y}%")

Maps & geojson

data(worldgeojson)
data(GNI2010, package = "treemap")

head(GNI2010)

iso3	country	continent	population	GNI
ABW	Aruba	North America	108	0
AFG	Afghanistan	Asia	34385	410
AGO	Angola	Africa	19082	3960
ALB	Albania	Europe	3205	3960
ARE	United Arab Emirates	Asia	7512	0
ARG	Argentina	South America	40412	8620


highchart() %>% 
  hc_add_series_map(worldgeojson, GNI2010,
                    value = "GNI", joinBy = "iso3")

Other fun example. Load various geojson and chart them all.

library("httr")

world <- "https://raw.githubusercontent.com/johan/world.geo.json/master/countries.geo.json" %>% 
  GET() %>% 
  content() %>% 
  jsonlite::fromJSON(simplifyVector = FALSE)

# http://cedeusdata.geosteiniger.cl/layers/geonode:mundo_corrientes_maritimas
marine <- "http://cedeusdata.geosteiniger.cl/geoserver/wfs?srsName=EPSG%3A4326&typename=geonode%3Amundo_corrientes_maritimas&outputFormat=json&version=1.0.0&service=WFS&request=GetFeature" %>% 
  GET() %>% 
  content()

# http://cedeusdata.geosteiniger.cl/layers/geonode:mundo_limites_placas
plates <- "http://cedeusdata.geosteiniger.cl/geoserver/wfs?srsName=EPSG%3A4326&typename=geonode%3Amundo_limites_placas&outputFormat=json&version=1.0.0&service=WFS&request=GetFeature" %>% 
  GET() %>% 
  content()

# http://cedeusdata.geosteiniger.cl/layers/geonode:mundo_volcanes
volcano <- "http://cedeusdata.geosteiniger.cl/geoserver/wfs?srsName=EPSG%3A4326&typename=geonode%3Amundo_volcanes&outputFormat=json&version=1.0.0&service=WFS&request=GetFeature" %>% 
  GET() %>% 
  content()

highchart(type = "map", debug = TRUE) %>% 
  hc_add_series(mapData = world, showInLegend = FALSE) %>% 
  hc_add_series(data = marine, type = "mapline",  lineWidth = 2,
                name = "Marine currents", color = 'rgba(0, 0, 80, 0.5)',
                states = list(hover = list(color = "#BADA55")),
                tooltip = list(pointFormat = "{point.properties.NOMBRE}")) %>%
  hc_add_series(data = plates, type = "mapline",
                name = "Plates", color = 'rgba(10, 10, 10, 0.5)',
                tooltip = list(pointFormat = "{point.properties.TIPO}")) %>% 
  hc_add_series(data = volcano, type = "mappoint",
                name = "Volcanos", color = 'rgba(255, 0, 80, 0.5)',
                tooltip = list(pointFormat = "{point.properties.NOMBRE}")) %>%
  hc_mapNavigation(enabled = TRUE) %>% 
  hc_title(text = "Testing geojson format")

`hchart()` function

Right now there are some R object to plot wiht this generic function.

Think like ggplot. The resulting chart is a highchart object so you can modify attributes like titles, tootlips or add themes.

Numeric

x <- c(rnorm(500), rnorm(500, 6, 2))
class(x)
## [1] "numeric"
hist(x, breaks = "FD") # by default hchart use *Freedman-Diaconis* rule

hchart(x)

Histogram

x <- hist(rbeta(300, 0.2, 4), plot = FALSE)
class(x)
## [1] "histogram"
plot(x) # by default hchart use *Freedman-Diaconis* rule

hchart(x)

Character, Factor

data(diamonds, package = "ggplot2")
x <- diamonds$cut
class(x)
## [1] "ordered" "factor"
plot(x)

hchart(x)

hchart(as.character(x), type = "pie")

ts

x <- LakeHuron
class(x)
## [1] "ts"
plot(x)

hchart(x)

xts quantmod package

library("quantmod")
x <- getSymbols("USD/JPY", src = "oanda", auto.assign = FALSE)
class(x)
## [1] "xts" "zoo"
plot(x)

hchart(x)

xts ohlc

x <- getSymbols("YHOO", auto.assign = FALSE)
class(x)
## [1] "xts" "zoo"
plot(x)

hchart(x)

acf(s)

x <- acf(diff(AirPassengers), plot = FALSE)
class(x)
## [1] "acf"
plot(x)

hchart(x)

Multivariate Time series

x <- cbind(mdeaths, fdeaths)
class(x)
## [1] "mts"    "ts"     "matrix"
plot(x)

hchart(x)

Distance matrix

x <- dist(mtcars[ order(mtcars$hp),])
class(x)
## [1] "dist"
plot(x)

hchart(x)

Themes

hc <- highchart() %>% 
  hc_title(text = "Motor Trend Car Road Tests") %>% 
  hc_subtitle(text = "Source: 1974 Motor Trend US magazine") %>% 
  hc_xAxis(title = list(text = "Weight")) %>% 
  hc_yAxis(title = list(text = "Miles/gallon")) %>% 
  hc_chart(zoomType = "xy") %>% 
  hc_add_series_scatter(mtcars$wt, mtcars$mpg,
                       mtcars$drat, mtcars$hp,
                       rownames(mtcars),
                       dataLabels = list(
                         enabled = TRUE,
                         format = "{point.label}"
                       )) %>% 
  hc_tooltip(useHTML = TRUE,
             headerFormat = "<table>",
             pointFormat = paste("<tr><th colspan=\"1\"><b>{point.label}</b></th></tr>",
                                 "<tr><th>Weight</th><td>{point.x} lb/1000</td></tr>",
                                 "<tr><th>MPG</th><td>{point.y} mpg</td></tr>",
                                 "<tr><th>Drat</th><td>{point.z} </td></tr>",
                                 "<tr><th>HP</th><td>{point.valuecolor} hp</td></tr>"),
             footerFormat = "</table>")

Default

hc

Dark Unica

hc %>% hc_add_theme(hc_theme_darkunica())

Grid Light

hc %>% hc_add_theme(hc_theme_gridlight())

Sand Signika

hc %>% hc_add_theme(hc_theme_sandsignika())

Chalk

Insipired in https://www.amcharts.com/inspiration/chalk/

hc %>% hc_add_theme(hc_theme_chalk())

Null

hc %>% hc_add_theme(hc_theme_null())

Customs

thm <- hc_theme(
  colors = c('red', 'green', 'blue'),
  chart = list(
    backgroundColor = NULL,
    divBackgroundImage = "http://media3.giphy.com/media/FzxkWdiYp5YFW/giphy.gif"
  ),
  title = list(
    style = list(
      color = '#333333',
      fontFamily = "Erica One"
    )
  ),
  subtitle = list(
    style = list(
      color = '#666666',
      fontFamily = "Shadows Into Light"
    )
  ),
  legend = list(
    itemStyle = list(
      fontFamily = 'Tangerine',
      color = 'black'
    ),
    itemHoverStyle = list(
      color = 'gray'
    )   
  )
)

hc %>% hc_add_theme(thm)

Merge Themes

thm <- hc_theme_merge(
  hc_theme_darkunica(),
  hc_theme(
    chart = list(
      backgroundColor = "transparent",
      divBackgroundImage = "http://cdn.wall-pix.net/albums/art-3Dview/00025095.jpg"
    ),
    title = list(
      style = list(
        color = 'white',
        fontFamily = "Erica One"
      )
    )
  )
)

hc %>% hc_add_theme(thm)

More Examples

Highcharts home page example

Example in http://www.highcharts.com/

rainfall <- c(49.9, 71.5, 106.4, 129.2, 144, 176,
              135.6, 148.5, 216.4, 194.1, 95.6, 54.4)

temperature <- c(7, 6.9, 9.5, 14.5, 18.2, 21.5,
                 25.2, 26.5, 23.3, 18.3, 13.9, 9.6)

col1 <- hc_get_colors()[3]
col2 <- hc_get_colors()[2]

highchart() %>% 
  hc_title(text = "Tokyo Climate") %>% 
  hc_legend(enabled = FALSE) %>% 
  hc_xAxis(categories = month.abb) %>% 
  hc_yAxis(
    list(
      title = list(text = "Temperature"),
      align = "left",
      showFirstLabel = FALSE,
      showLastLabel = FALSE,
      labels = list(format = "{value} &#176;C", useHTML = TRUE)
    ),
    list(
      title = list(text = "Rainfall"),
      align = "right",
      showFirstLabel = FALSE,
      showLastLabel = FALSE,
      labels = list(format = "{value} mm"),
      opposite = TRUE
    )
  ) %>% 
  #
  hc_tooltip(formatter = htmlwidgets::JS("function(){
                                         if('Sunshine' == this.series.name){
                                         return  '<b>' + this.point.name + ': </b>' + this.y
                                         } else {
                                         unts = this.series.name == 'Rainfall' ? 'mm' : '&#176;C';
                                         return (this.x + ': ' + this.y + ' ' + unts)
                                         }}"),
             useHTML = TRUE) %>% 
  hc_add_series(name = "Rainfall", type = "column",
                data = rainfall, yAxis = 1) %>% 
  hc_add_series(name = "Temperature", type = "spline",
                data = temperature) %>% 
  hc_add_series(name = "Sunshine", type = "pie",
                data = list(list(y = 2020, name = "Sunshine hours",
                                 sliced = TRUE, color = col1),
                            list(y = 6740, name = "Non sunshine hours (including night)",
                                 color = col2,
                                 dataLabels = list(enabled = FALSE))),
                center = c('20%', 45),
                size = 80)

Heatmap

nyears <- 5

df <- expand.grid(seq(12) - 1, seq(nyears) - 1)
df$value <- abs(seq(nrow(df)) + 10 * rnorm(nrow(df))) + 10
df$value <- round(df$value, 2)
ds <- list.parse2(df)

hc <- highchart() %>% 
  hc_chart(type = "heatmap") %>% 
  hc_title(text = "Simulated values by years and months") %>% 
  hc_xAxis(categories = month.abb) %>% 
  hc_yAxis(categories = 2016 - nyears + seq(nyears)) %>% 
  hc_add_series(name = "value", data = ds)

hc_colorAxis(hc, minColor = "#FFFFFF", maxColor = "#434348")


require("viridisLite")

n <- 4
stops <- data.frame(q = 0:n/n,
                    c = substring(viridis(n + 1), 0, 7))
stops <- list.parse2(stops)

hc_colorAxis(hc, stops = stops, max = 75)

Treemap

data(diamonds, package = "ggplot2")

df <- dplyr::count(diamonds, cut)
df

cut	n
Fair	1610
Good	4906
Very Good	12082
Premium	13791
Ideal	21551


df <- setNames(df, c("name", "value"))
ds <- list.parse3(df)

highchart() %>% 
  hc_title(text = "A simple Treemap") %>% 
  hc_add_series(data = ds, type = "treemap", colorByPoint = TRUE)

Creating a chart from a list of parameters

Similar input like chordEx1 example in http://yihui.name/recharts/

Example 1

hc_opts <- list()
hc_opts$title <- list(text = "This is a title", x = -20)
hc_opts$xAxis <- list(categories = c('Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun',
                                     'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec'))
hc_opts$series <- list(list(name = "Tokyo",
                            data = c(7.0, 6.9, 9.5, 14.5, 18.2, 21.5,
                                     25.2, 26.5, 23.3, 18.3, 13.9, 9.6)))

hc_opts$series <- append(hc_opts$series,
                         list(list(name = "New York",
                                   type = "spline",
                                   lineWidth = 5,
                                   data = c(-0.2, 0.8, 5.7, 11.3, 17.0, 22.0,
                                            24.8, 24.1, 20.1, 14.1, 8.6, 2.5),
                                   dataLabels = list(align = "left", enabled = TRUE))))

highchart(hc_opts)

Example 2

hc_opts <- list()
hc_opts$chart <- list(type = "bar")
hc_opts$title <- list(title = "Stacked bar")
hc_opts$xAxis <- list(categories = c('Apples', 'Oranges', 'Pears', 'Grapes', 'Bananas'))
hc_opts$yAxis <- list(min = 0, title = list(text = 'Total Fruit Consumtion'))
hc_opts$legend <- list(reversed = TRUE)
hc_opts$series <- list(list(name = "John", data = c(5, 3, 4, 7, 2)),
                       list(name = "Jane", data = c(2, 2, 3, 2, 1)),
                       list(name = "Joe", data = c(3, 4, 4, 2, 5)))

highchart(hc_opts, theme = hc_theme_darkunica())

highcharter: Just another Highcharts wrapper for R

Joshua Kunst